A new signal fault detection algorithm for vector tracking loop in strong noise environments

Abstract

In the vector tracking loop(VTL) of the satellite navigation system, the signal faults caused by the abnormal atmospheric disturbances or other interferences may be distorted when outputted by the discriminators, due to the nonlinearities in the discriminators. This makes the large bias faults in strong noise environments hard to detect and then the navigation solution may be contaminated. A new signal fault detection algorithm for VTL in strong noise environments is proposed in this paper to deal with this issue. Firstly, the reason and effects of distortion that occurs on discriminator output are analyzed. Then a new code discriminator is designed for signal fault detection, which owns a wider positive correlation output range about the code tracking error thus improving the detection ability for large abrupt bias faults and drift faults in strong noise environments. Later a third-degree spherical-radial cubature rule is employed to estimate the test statistic and its variance matrix. Finally, comparison trials about abrupt faults and drift faults in different noise environments illustrate that the proposed algorithm maintains reliable detection ability about abrupt faults that are larger than 0.5 chips and can detect drift faults in 25~30 dBHz strong noise environments.

Keywords

• vector tracking
• fault detection
• kalman filter
• code discriminator
• spherical-radial cubature rule